We developed a machine learning model to quantify cardiac fibrosis (which is associated with cardiovascular disease) using cardiac MRI data from 41,505 UK Biobank participants. In the subsequent large-scale GWAS of cardiac fibrosis, we identified 11 independent genomic loci, 9 of which were implicated in in vitro cardiac fibroblast activation.
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References
López, B. et al. Diffuse myocardial fibrosis: mechanisms, diagnosis and therapeutic approaches. Nat. Rev. Cardiol. 18, 479–498 (2021). A comprehensive review article on the mechanisms, diagnosis and therapeutic approaches for diffuse myocardial fibrosis.
Tam, V. et al. Benefits and limitations of genome-wide association studies. Nat. Rev. Genet. 20, 467–484 (2019). A review article that critically appraises the strengths and limitations of GWAS.
Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018). A review article that describes the UK Biobank recruitment protocol and the deep phenotyping of study participants.
Diao, K. et al. Histologic validation of myocardial fibrosis measured by T1 mapping: a systematic review and meta-analysis. J. Cardiovasc. Magn. Reson. 18, 92 (2017). A meta-analysis providing evidence validating the use of non-invasive T1 mapping as a surrogate for histological assessment of myocardial fibrosis.
Treibel, T. A. et al. Extracellular volume associates with outcomes more strongly than native or post-contrast myocardial T1. JACC Cardiovasc. Imaging 13, 44–54 (2020). This paper presents evidence supporting the use of extracellular volume fraction for MRI-based fibrosis quantification as a more sensitive marker with stronger associations with disease than T1 time.
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This is a summary of: Nauffal, V. et al. Genetics of myocardial interstitial fibrosis in the human heart and association with disease. Nat. Genet. https://doi.org/10.1038/s41588-023-01371-5 (2023).
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Machine learning to examine the genetic underpinnings of cardiac fibrosis at scale. Nat Genet 55, 736–737 (2023). https://doi.org/10.1038/s41588-023-01369-z
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DOI: https://doi.org/10.1038/s41588-023-01369-z
